The present invention relates to computer-based locating and tracking of objects such as vehicles, vessels, aircraft, bicycles, animals, and containers.
Automatic Vehicle Location System (AVL) has been a known technology since the completion of the NAVSTAR Global Positioning System (GPS) by the US Department of Defense. A typical AVL consists of (1) one or more mobile units, (2) one or more vehicle monitoring stations, and (3) a wireless communication network. A mobile unit is a piece of hardware with a GPS receiver and a wireless transmitter installed in a vehicle. A vehicle monitoring station has the computer equipment to process GPS data and monitor vehicle locations. The wireless communication network is used to send vehicle GPS data from a mobile unit to a monitoring station.
Location information of any object can be obtained from a GPS receiver or other terrestrial location-detection device. The location information is typically represented by either latitude/longitude (denoted as lat/long in the GIS and mapping industry), or a pair of x and y coordinates using any local referencing system (denoted as x-y). In addition to lat/long or x-y, additional information about any object can include speed, direction of movement if the object is moving, and elevation. Furthermore, each location record can be associated with the time and date the object location was recorded.
The location information obtained from the object is typically transmitted through a wireless communication network to a centralized location for data processing. Such a location is usually called the AVL Host, Data Processing Center, or Data Processing Station, where AVL stands for Automatic Vehicle Location system. A Host and one or more Mobile Units are equipped with the location-detection device. The usual systems of the prior art handle location information by displaying the location of the Mobile Unit on a digital map in the same coordinate system (lat/long or x-y) as a dot. An operator interprets the location by referencing surrounding features on the map, such as streets, landmarks, buildings, parks, etc. Translation of the point location of the object into a more useful expression of map location is thus processed manually by the operator.
Major limitations of the prior art include:
(1) The Host computer is installed with mapping software to display both the object location and the reference map.
(2) An operator reads the map and translates the location information into other descriptive forms.
(3) If a user of the service desires to know the location of the object being tracked, the operator may verbally describe the location information to the user, or send the user a text file describing the location, or send the user a map in either digital form or hard copy map.
(4) If the user intends to retrieve the location information with a thin client receiver, the choices are quite limited. First, if the user has an analog cellular phone, then the operator must describe the location to the user by voice communication. In this case, sending a text file or a digital map is not an option. A hard copy map is out of question. Second, if the user has a computer of any kind with a modem or Internet connection, then the operator can either send a text file describing the location, or send a digital map showing the location of the object against the referencing map. Third, if the user has a hand-held computer with a modem or other form of wireless communication, then the receiving method could be either a text file or a digital map. Fourth, if the user has a hand-held computer, or a mobile data terminal, then the only option is a text file describing the location of the object. A cellular phone with limited image display capability can also receive a text file as in the fourth case.
The current method thus has the following major constraints:
(1) The process requires manual operations at the Host or the Data Processing Center.
(2) Manually interpreting location information is time consuming and error-prone.
(3) Due to the required manual processing, tracking of objects is not done in real-time.
(4) Because of the above constraints, currently it is not practical to receive location information through thin-clients such as cellular phones or hand-held computers.
Geocoding, also known as address matching, is the process of translating a street address into a set of map coordinates. For example, the input of xe2x80x9c1234 Main Street, Columbus,xe2x80x9d is translated into a pair of Latitude and Longitude readings, or X and Y coordinates, so that the location of that address can be displayed on a map. Reverse Geocoding is opposite to geocoding. It takes a pair of Latitude and Longitude, or X and Y coordinates, and converts the input coordinates into a street address. There are two known methods of reverse geocoding, the Polygon method and the Centroid method. The Centroid method is a revised and enhanced version of the Polygon method.
The Polygon method is based on polygons of a parcel map, i.e., each land record is digitized into a polygon representing the parcel, and the record is associated with a street address. Conceptually, any point location denoted by a pair of Lat/Long or X-Y can be plotted on the parcel map and then the parcel in which the point location falls is identified and the address determined. There are two major problems with the Polygon method. First, parcel maps showing polygon features tend to be excessively large in size even for just a small city. Data processing is extremely difficult due to the file size. As a consequence, the Polygon method is just a concept and is not used practically. Empirical application of this method is limited to small geographic areas. Second, digital parcel maps are expensive to build and are available only in very few cities or counties. Using this method for reverse geocoding is thus feasible in only a very few cases.
The Centroid method is basically a revision of the Polygon method and the enhancement is meant to reduce the file size substantially. Instead of using polygons to represent parcels, the Centroid method organizes land records by the centroid location of each parcel and the centroid point becomes the graphical object in the database. As each polygon is reduced to a point location, the file size is minimized. The search method can be much improved with the Centroid method. In the Polygon method, the program must compare the target point location with polygons. The Centroid method only needs to find the closest centroid point from the target point. The Centroid method still requires a parcel map, and must convert the parcel map into a point coverage of centroid locations, which requires one additional procedure in data preparation. The main problem remains the same, i.e., polygon maps are available only in very few areas. An additional problem is that an incorrect parcel can be associated with the target point location, particularly when the parcel sizes are not uniform.
Both the Polygon method and the Centroid method face major limitations. In practical terms, the required parcel maps are not available in most cities or counties. In terms of methodology, the major limitation is that the information that can be generated from either method is limited to the street address of the best-fit location and is not related to the street network. For instance, the result of one match could be xe2x80x9c1234 Main Street, Santa Ana, Calif.xe2x80x9d. In reality, the point location obtained from GPS satellites is not accurate. At present, after the US government removed the introduced error called Selective Availability (SA) on May 1, 2000, the point is within 10 meters accuracy, meaning that the location could be 10 meters off the actual location. In addition, if the digital map has a 20-meter accuracy, then the worst case position discrepancy could be 30 meters.
Due to the above limitations, the existing methods cannot generate information about street networks. Either method can generate a best-fit address, but it cannot tell us whether the object is between a pair of intersections. Furthermore, the object may be placed at a location on the wrong side of a freeway, i.e., if the object is moving south-bound on a limited access freeway, either method may place it on the north bound lane without knowing whether the match is correct or not.
Thus there is a critical need for a tracking system that can operate in real-time without operator intervention, that can automatically service thin-clients, and that otherwise overcomes the disadvantages of the prior art.
The present invention meets this need by providing a system and method that is particularly effective in tracking objects in real-time, allowing thin-client receivers, such as cellular phones or hand-held computers, to receive location information of any object being tracked in real-time. In one aspect of the invention, a system for tracking objects in an environment having geographical reference features includes database for storing reference data as line segments corresponding to coordinate locations along the reference features; means for receiving object data including respective target points as coordinate locations of the objects; and a computer having access to the database and to the object data, the computer being programmed for generating an interpreted location of each of the objects in terms relative to automatically selected ones of the reference features.
The means for receiving object data can include a plurality of mobile units for connection to respective ones of the objects, each of the mobile units having means for receiving signals from an external location system and generating the object data, and a wireless transmitter for transmitting the object data over a wireless communication network for access by the computer. The means for receiving signals can include a GPS receiver. The object data can further include a target altitude. The means for receiving signals can include a terrestrial position receiver having access to a terrestrial location system. The object data can further include object identification. The object data can further include a target velocity. The object data can further include a target heading.
The database can be sectioned by geographic unit, the computer being programmed for determining geographic units containing the coordinate locations of the objects and, for each of the objects, accessing a corresponding section of the database. The database sections can include digital street maps, the computer being programmed for determining at least some of the interpreted locations in terms of a closest street, an intersecting street, and a direction on the closest street from the intersecting street. At least some of the interpreted locations can further include a closest location along the closest street. At least some of the interpreted locations can further include a heading and distance from the closest location. The determination of the closest street can be qualified to exclude streets that are inconsistent with a velocity and heading of the object. At least one of the velocity and heading of the object can be determined based on separately received target points of the object and a time interval between the target points.
The system can further include means for temporarily saving segments of excluded streets as reserve segments, means for determining a likelihood of abnormal object movement, and means for restoring the reserve segments as candidate segments following a determination of abnormal object movement. The means for determining abnormal object movement can include means for determining that, for any target point, there are only reserve segments.
In another aspect of the invention, a system for tracking objects in an environment having geographical reference features includes the database for storing reference data corresponding to coordinate locations along the reference features; the means for receiving object data including coordinate locations of the objects; the computer having access to the database and to the object data, the computer being programmed for generating an interpreted location of each of the objects in terms relative to selected ones of the reference features, the interpreted locations being in a plurality of formats selected from the set consisting of text, high-resolution graphics, low-resolution graphics, analog voice, and digital voice; the computer also being interfaced to a data communication network being accessible by network terminals including thin-client receivers; and the computer being further programmed for determining from a requesting network terminal a capability of that terminal for receiving any of the plurality of formats, and automatically transmitting the interpreted location of an identified object in a compatible one of the selected formats.
In a further aspect of the invention, a method for tracking objects in an environment having geographical reference features in terms relative to automatically selected ones of the reference features includes the steps of:
(a) providing a database for storing reference data as line segments corresponding to coordinate locations along the reference features;
(b) receiving object data including a target point as a coordinate location of one of the objects;
(c) defining an initial target zone proximate the target point;
(d) determining whether a predetermined number of the line segments extend within the target zone;
(e) in the absence of the predetermined number, enlarging the target zone and repeating step (d);
(f) identifying as candidate segments the line segments extending within the target zone;
(g) selecting a matching segment from the candidate segments;
(h) calculating a matching point on the matching segment, the matching point being in closest proximity to the object location; and
(i) interpreting the object location in terms of the matching segment and the matching point.
The selecting of the matching segment can include exclusion of segments from the candidate segments based on one or more of physical attributes of the reference features represented by the line segments, velocity of the object, heading of the object, a last previously identified matching segment, and previously identified location(s) of the object. The selecting of the matching segment can further include determining a closest segment from remaining candidate segments. The determination of the matching segment can be qualified to exclude segments that are inconsistent with a velocity and heading of the object. The method can further include determining at least one of the velocity and heading of the object based on separately received target points of the object and a time interval between the target points. The method can further include temporarily saving segments of excluded streets as reserve segments, determining a likelihood of abnormal object movement, and restoring the reserve segments as candidate segments following a determination of abnormal object movement. The determination of abnormal object movement can include determining that, for any target point, there are only reserve segments.
The method can further include determining a boundary feature from which to access the matching point, including determining whether the matching segment terminates in an intersection, an end, and/or a continuation segment; for terminations exclusive of intersections and ends, substituting the continuation segment and repeating step (a); and including the end and intersection(s) in the interpreting of the object location. The method can further include monitoring a data communication network; receiving an object location request from a client of the data communication network; automatically identifying a data output capability of the client; automatically selecting an output format for the object location interpretation, the output format being consistent with the data output capability of the client; and transmitting the location interpretation in the selected output format.
The database can be sectioned by geographic unit, the method further including determining geographic units containing the coordinate locations of the objects and, for each of the objects, accessing a corresponding section of the database. The database sections can include digital street maps, the method further including determining at least some of the interpreted locations in terms of a closest street, an intersecting street, and a direction on the closest street from the intersecting street.
In yet another aspect, the invention is embodied in a computer program embodied on a computer-readable medium and having code segments for tracking objects according to the above-described method.